The First IEEE International Conference on Artificial Intelligence Testing (2019 IEEE AITest)

Artificial Intelligence (AI) technologies are widely used in computer applications to perform tasks
such as monitoring, forecasting, recommending, prediction, and statistical reporting. They are deployed
in a variety of systems including driverless vehicles, robot controlled warehouses, financial forecasting
applications, and security enforcement and are increasingly integrated with cloud/fog/edge computing, big
data analytics, robotics, Internet-of-Things, mobile computing, smart cities, smart homes, intelligent
healthcare, etc. However, the quality assurance of existing AI application development processes
is still far from satisfactory and the demand for being able to show demonstrable levels of confidence
in such systems is growing. Software testing is a fundamental, effective and recognized quality assurance
method which has shown its cost-effectiveness to ensure the reliability of many complex software-systems.
However，the adaptation of software testing to the peculiarities of AI applications remains largely
unexplored and needs extensive research to be performed. On the other hand, the availability of
AI technologies provides an exciting opportunity to improve existing software testing processes,
and recent years have shown that machine learning, data mining, knowledge representation, constraint
optimization, planning, scheduling, multi-agent systems, etc. have real potential to positively
impact on software testing. Recent years have seen a rapid growth of interests in testing
AI applications as well as application of AI techniques to software testing. It is, therefore,
timely to provide an international forum for researchers and practitioners to exchange novel
research results, to articulate the problems and challenges from practices, to deepen our understanding
of the subject area with new theories, methodologies, techniques, processes models, etc., and to
improve the practices with new tools and resources. This is the aim of the IEEE conference on AI
Testing.

Topics of Interest

The conference invites papers of original research on AI testing and reports of the
best practices in the industry as well as the challenges in practice and research.
Topics of interest include (but are not limited to)
the following:

Testing AI applications

Methodologies for testing, verification and validation of AI applications

Genetic algorithms, search-based techniques and heuristics to
optimization of testing

Knowledge-based and expert systems for software testing

Data quality checking for AI applications

Testing and quality assurance for unstructured training data

Automatic validation tool for training unstructured data and big data

Large-scale unstructured data quality certification

Format

Regular Paper Format

We primarily invite submission of research papers, that describe original and
significant work, but also papers which reports on case studies and empirical research.
Papers must not be accepted for publication, or be under submission to another
conference or journal. Each paper will be reviewed by at least three members of the
Program Committee, using a single-blind reviewing procedure.
All papers must be submitted electronically using the EasyChair conference system in PDF
format. Each paper is limited to 8 pages including figures and references using IEEE
Computer Society Proceedings (two columns, single-spaced, 10pt font).
At least one of the authors of any accepted paper would have to register for the
conference and confirm that she/he will present the paper in person.